S+


S+ software provides point/click access to advanced graphics and cutting edge statistics,
without coding in R.

From A$4,200/user/year + gst

S+ Software


 S+ contains the most comprehensive library of statistical & mathematical algorithms available.

S+ FinMetrics library

Advanced econometric modeling

S+ FinMetrics is an advanced library for modeling, analyzing, and visualizing financial market data. The library includes times-series, GARCH, State-Space, multifactor modelling and much more.

S+ NuOPT library

Cutting Edge Numerical Optimisation

NuOPT is a sophisticated optimization package with the ability to efficiently solve linear and nonlinear optimization problems with thousands of variables and constraints.

Designed to solve a wide range of problems, from linear programming through Mixed Integer Programming (MIP) to constrained nonlinear optimization. Offering state of-art primal dual interior point methods, SIMPLEX, sequential quadratic programming and active set methods. Ensures efficient optimal solutions for both small and large problems.

S+ Bayesian modelling library

FlexBayes provides tools for modeling data using the Bayesian paradigm for statistical inference.

Bayesian modeling can create more realistic models, provide a natural way to address missing data and take advantage of prior information when doing analysis.

Create better clinical trial designs. Improve portfolio management and enhance many other applications. Additionally, the library includes built in examples of Bayesian response-adaptive clinical trial design, safety data analysis and hierarchical generalized linear models.

S+ Market Basket Analysis

S+ Software includes Association Rules, which help uncover relationships between variables in large data sets.

Detect purchase patterns with Market Basket Analysis or analyse web site usage.

S+ Resample library

S+ Resample library offers a variety of resampling techniques, such as bootstrap and permutation tests, which enable the use of standard statistics on smaller data sets. Offers graphical and numerical diagnostics for standard statistical assumptions.

Additionally, bootstrap tilting is included, which provides very accurate intervals and requires fewer samples than other methods.

S+ Wavelets library

Wavelets library provides advanced signal and image analysis, time series analysis, statistical signal estimation and data compression analysis.

Spatial Statistics software library

SpatialStats enables the exploration and modeling of spatially correlated data, which is useful in many areas such as environmental sciences, mining and petroleum engineering, natural resources management, geography, epidemiology, and demographics.

Environmental Statistics library

EnvironmentalStats provides a set of powerful functions for performing graphical and statistical analyses of environmental data.

Useful for anyone who has to make sense of environmental data, including hydrologists, soil scientists, atmospheric scientists, geochemists, environmental engineers, hazardous and solid waste site managers, regulatory agency analysts and enforcement officers.

Feature List

Convenient window-based GUI with easy-to-use menus and dialogs

  • File import and export dialogs
  • Database import and export dialogs¹
  • Dialogs for data preparation, charting and statistical modeling
  • Interactive command-line with history recall
  • Manage objects with Object Explorer¹
  • Script file editor¹
  • Multiple data and graphics windows
  • Cut-and-paste to Word, PowerPoint and Excel¹
  • Integrated Excel spreadsheets¹
  • PowerPoint Wizard: quickly create slides from charts¹
  • Create custom toolbars, menus and dialogs¹
  • On-line help and manuals

Integrate with many data and graphics formats

  • ASCII: fixed format, comma-separated, and tab-delimited
  • Spreadsheets: Excel, Lotus 1-2-3, Quattro Pro
  • Application data: SAS 7/8/9, SPSS, Matlab, Minitab, Sigma Plot, Systat, STATA, Gauss, Epi Info and more
  • Database files: Paradox, dBase, Access, FoxPro
  • Financial data sources: LIM, Bloomberg, FAME
  • Native database clients: SQL Server¹, Oracle, Sybase, IBM DB2
  • ODBC interface to compliant databases
  • Read and write Spotfire binary and text files directly, helping to preserve important metadata when moving between applications.
  • Export graphics as PDF, PostScript, GIF, PNG, JPG, WMF, bitmap, TIFF and more
  • Customised, automated reports: XML reporting library speeds development of customized reports incorporating statistical tables and publication-quality graphics.

Create custom graphics

  • Interactive graphics system with a large & normalized palette for the creation of statistical charts to your exact specifications.
  • Scatterplots, histograms, pie charts, box plots, bar charts, dot charts, time series charts, 3-D wireframe charts, image plots and many more.
  • Brush and spin dynamic visualization
  • Programmatic control over colors, lines, axes, annotations and layout
  • Unique Trellis™ graphics – create multiple charts conditioned by levels of one or more variables
  • Create interactive, embedded web-based charts with S‑PLUS Graphlets™
  • Element-Specific Graph arguments for plots and command-line graphics

Hypothesis Tests and Confidence Intervals 

  • One-sample and two-sample t-test and Wilcoxon
  • Paired t-test
  • Correlation: Pearson, Kendall’s tau, Spearman’s rho
  • Goodness-of-Fit: Chi-square, Kolmogorov-Smirnov, Shapiro-Wilk
  • Rank tests: Kruskal-Wallis, Friedman
  • Proportions: exact Binomial test, Normal approximation
  • Contingency tables and tests for independence: Chi-square, Fisher, Mantel-Haenszel, McNemar

Regression

  • Basic linear regression
  • Polynomial regression
  • Model diagnostics
  • Prediction and confidence intervals
  • Stepwise selection of models
  • Parametric spline models
  • Constrained regression
  • Logistic regression
  • Generalized linear models

Analysis of Variance

  • Univariate and multivariate ANOVA
  • Flexible specification of variables, covariables, interactions, nesting, transformations
  • Automatic generation of dummy variables
  • Choice of contrasts
  • Type III sums of squares
  • Designed experiments: one-way, two-way, factorial, split-plot, unbalanced, fractional factorial designs, response surface methods, robust designs, taguchi methods and more
  • Variance component estimation
  • Multiple comparisons: Fisher, Tukey, Dunnett, Sidak, Bonferroni, Scheffé, simulation-based

Nonlinear Regression and Maximum Likelihood

  • Nonlinear regression
  • Nonlinear maximum likelihood
  • Quasi-likelihood
  • Constrained nonlinear regression

Nonparametric Regression

  • Generalized additive models (GAMs)
  • Smoothers: loess, super, kernel, spline
  • Projection Pursuit, ACE, and AVAS

Tree Models

  • Classification trees
  • Regression trees
  • Pruning, shrinking, and splitting
  • Scoring

Correlated Data Analysis

  • Longitudinal data and repeated measures analysis
  • Linear (LME), nonlinear (NLME), and generalized mixed effects (GLMM) models
  • Generalized Estimating Equations (GEE)
  • Biexponential, first-order compartment, four-parameter logistic models
  • User-defined correlation structures

Resampling

  • Bootstrap
  • Jackknife

Multivariate Analysis

  • Canonical correlation
  • Discriminant analysis
  • Factor analysis
  • Multidimensional scaling
  • Principal components
  • Biplots

Cluster Analysis

  • K-means
  • Hierarchical clustering
  • Monothetic clustering
  • Model-based clustering
  • Crisp and fuzzy clustering
  • Divisive and agglomerative methods

Quality Control

  • Shewhart chart
  • Cusum chart
  • Charts based on xbar, s, np, p, c, u

Power and Sample Size

  • Normal mean
  • Binomial proportion

Survival Analysis

  • Kaplan-Meier curves
  • Cox proportional hazards models with mixed effects
  • Left, right, and interval censoring
  • Time-dependent covariates and strata
  • Multiple event models
  • Competing risk models
  • Frailty models
  • Parametric survival
  • Expected survival
  • Person years analysis
  • Aalen’s Additive Regression Model

Time Series Analysis 

  • Autocovariance, autocorrelation and partial autocorrelation
  • Smoothed periodograms
  • Box-Jenkins ARIMA models
  • Classical and robust AR
  • Long-memory models
  • Seasonal decompositions
  • Fourier transformations
  • Classical and robust smoothers and filters

Robust Statistics

  • Robust estimation and inferences
  • Robust MM regression
  • Robust GLM, ANOVA, covariance, principal components, and discriminant analysis
  • Least trimmed squares regression
  • Minimum absolute residual regression
  • Visually compare robust and traditional methods

Missing Data

  • Multiple imputation
  • Gaussian, logistic, and conditional Gaussian models

Date, Time, and Calendar Data

  • Univariate and multivariate time series
  • Aggregation, alignment, merging, and interpolation
  • Times and dates from milliseconds to millennia
  • Time zones with international daylight savings rules
  • Holidays and financial market closures
  • Custom time and date formats
  • Relative time, time sequence, and event objects
  • Powerful time-series charting

Mathematical Computations

  • Vector and matrix algebra
  • Matrix decompositions
  • Systems of linear equations
  • Locate roots
  • Nonlinear optimization
  • Constrained optimization
  • Ordinary differential equations
  • Numerical integration

APIs and system interfaces

  • APIs for C, C++, Java and Fortran
  • Language support for pipes, sockets, and files
  • DDE, COM and OLE interfaces¹
  • XML import and export
  • Reporting in XML, PDF, HTML and RTF

Support for 64-bit platforms

  • S+ 8.2 is focused on helping customers scale their analyses to solve larger analytic problems
  • Perform large analyses entirely in memory
  • 64-bit support also improves the performance of very large analyses (S+ Big Data Library) by enabling larger chunks of data to be handled in each pass through the data
  • Matrix operations which underlie many common statistical methods are much faster in S+ 8.2 than in previous versions—up to 40x faster
  • Hexagonal binning plots to explore structure of large data sets
  • Data types for out-of-memory vectors, data frames, and time series

Award-winning S programming language

  • Specifically for exploratory data analysis and statistical modeling
  • Object-oriented, interpreted 4GL language
  • Interactive exploration and fast prototyping
  • Rich data structures: vector, matrix, array, data frame, list and many more
  • User-defined functions, objects, classes, methods and libraries
  • Library of over 4000 functions for data manipulation, graphics, statistical modeling, and integration

Additional libraries included

System Requirements
Processor2GHz or faster, Quad core  
(1 GHz, Dual core, minimum)
Hard Disk 500 MB of disk space to install
(If you are not installing on Drive C:\, an additional 50MB free disk space on Drive C:\ is required for the installation)
Administrator rights are required to install
Operating SystemMicrosoft® Windows 10
Microsoft® Windows 7 (32-bit and 64-bit)
Microsoft® Windows Vista® SP2 (32-bit & 64-bit)
Microsoft® Windows XP® SP3 (32-bit)
Parallels Desktop 15 for MacOS X 10.10 – 10.15